英语科技类阅读系列第9篇 — 算法

Text: 961 words

Category: computing

存眷 头条+西瓜+抖音号：杨老师STEAM教诲

Explainer: What is an algorithm? 解说员: 什么是算法?

Computers and others use these step-by-step rules to answer questions and process data.

盘算机和其他设置装备摆设利用这些循规蹈矩的规章来答复题目和处置惩罚数据

Back in the 9th century, a famous mathematician and astronomer made a lot of discoveries in science, math and the number system that we now use. His name was Muhammad ibn Mūsa al-Khwarizmī. His last name is Persian for the area of his birth: Khwãrezm. Over the centuries, as his fame grew, people outside the Middle East altered his name to Algoritmi. This version of his name would later be adapted as the English term that describes the step-by-step recipes we now known as algorithms.

早在9世纪，一位闻名的数学家和天文学家在科学、数学和我们如今利用的数字体系方面做出了许多发觉。他的名字叫穆罕默德-伊本-穆萨-赫瓦里兹米。他的姓是波斯语，表现他诞生的地域: 赫瓦里兹米。几个世纪以来，随着他的名气越来越大，中东以外的人把他的名字改为阿尔戈里特米。他的这个名字厥后被改编为英语术语，形貌我们如今所知的算法，就如一步一步做饭的食谱。

An algorithm is a precise step-by-step series of rules that leads to a product or to the solution to a problem. One good example is a recipe.

算法是一套准确的、循规蹈矩的规章，这些规章会导致产物或题目的办理方案。一个很好的例子便是食谱。

When bakers follow a recipe to make a cake, they end up with cake. If you follow that recipe precisely, time after time your cake will taste the same. But deviate from that recipe, even a little, and what emerges from the oven may disappoint your taste buds.

劈面包师根据食谱制作蛋糕时，他们终极得到的是蛋糕。假如你严厉根据这个食谱做，你的蛋糕尝起来照旧一样的。但假如偏离这个食谱，哪怕只是一点点，从烤箱里出来的工具大概会让你的味蕾绝望。

Some steps in an algorithm depend on what happened or was learned in earlier steps. Consider the cake example. Dry ingredients and wet ingredients might need to be combined in separate bowls before they can be mixed together. Similarly, some cookie batters must be chilled before they can be rolled out and cut into shapes. And some recipes call for the oven to be set to one temperature for the first few minutes of baking, and then changed for the rest of the cooking or baking time.

算法中的一些步调取决于在之前的步调中产生了什么或学到了什么。思量蛋糕的例子。干食材和湿食材大概必要在混淆之前分别在差别的碗中混淆。同样，一些饼干面糊在擀开和切成形状之前一定先冷却。有些食谱要求在烘焙的前几分钟将烤箱的温度设置为一个温度，然后在剩下的烹调或烘焙时间里转变温度。

We even use algorithms to make choices throughout the week.

我们乃至用算法来做选择

Let’s say you have an afternoon with nothing planned — no family activities, no chores. To settle on what to do, you will likely think through a series of smaller questions (or steps). For instance: Do you want to spend time alone or with a friend? Do you want to stay inside or go out? Do you prefer to play a game or watch a movie?

让我们假设你有一个没有打算的下战书没有家庭运动，没有家务。在决定要做什么时，你大概会思量一系列较小的题目(或步调)。比方:你想独处照旧和朋侪在一路?你想呆在家里照旧出去?你喜爱玩游戏照旧看影戏?

At each step you will consider one or more things. Some of your choices will depend on data you gathered from other sources, such as the weather forecast. Perhaps you realize that (1) your best friend is available, (2) the weather is warm and sunny, and (3) you’d love to play basketball. Then you might decide to go to a nearby park so the two of you can shoot hoops. At each step, you made a small choice that got you closer to your ultimate decision. (You can create a flowchart that lets you map the steps to a decision.)

每一步你都要思量一件或多件事变。您的一些选择将取决于您从其他泉源网络的数据，如气候预告。或许你意识到:(1)你最好的朋侪就在身边;(2)气候暖和、阳光绚烂;(3)你会喜爱打篮球。然后你大概会决定去周边的公园，如许你们两个就可以打篮球了。每一步，你都做了一个小的选择，让你更靠近终极的决定。(您可以创建一个流程图，以便将步调映射到决议计划。)

Computers use algorithms, too. These are the sets of instructions a computer program must follow in order. Instead of a step in a cake recipe (such as mix flour with baking powder), the computer’s steps are equations or rules.

盘算机也利用算法。这些是盘算机步伐一定按次序实行的指令集。电脑的步调不是制作蛋糕的步调(把面粉和发酵粉混淆)，而是方程式或规章。

Awash in algorithms 沉醉在算法里

Algorithms are everywhere in computers. The most well-known example might be a search engine, such as Google. To find the closest veterinarian that treats snakes or the fastest route to school, you might type the relevant question into Google and then review its list of possible solutions.

算法在盘算机中无处不在。最闻名的例子大概是搜刮引擎，比方谷歌。为了找到近来的治疗蛇的兽医或去学校的最快门路，你可以把相干的题目输入谷歌，然后检察大概的办理方案列表。

Mathematicians and computer scientists designed the algorithms that Google uses. They realized that searching the whole internet for the words in every question would take too long. One shortcut: Count the links between webpages, then give extra credit to pages with lots of links to and from other pages. Pages with more links to and from other pages will rank higher in the list of possible solutions that emerge from the search request.

数学家和盘算机科学家设计了谷歌利用的算法。他们意识到在整个互联网上搜刮每个题目的单词会耗费太多时间。一个快捷要领是:盘算网页之间的链接，然后给那些与其他网页有大量链接的页面分外加分。与其他页面有更多链接的页面将在搜刮恳求中显现的大概办理方案列表中排名更高。

Many computer algorithms seek new data as they work through a solution to some problem. A map app on a smartphone, for example, contains algorithms designed to find the fastest route or perhaps the shortest one. Some algorithms will connect to other databases to identify new construction zones (to avoid) or even recent accidents (which can tie up traffic). The app also may help drivers follow a chosen route.

很多盘算机算法在办理某些题目时查找新的数据。比方，智能手机上的一款舆图应用步伐包罗了旨在找到最快或最短门路的算法。一些算法将毗连到其他数据库，以辨认新的修建地区(以幸免)，乃至是近来的变乱(大概会阻塞交通)。该应用步伐还可以关心司机遵照选定的门路。

Algorithms can become complex as they gather lots of data from different sources to reach one or more solutions. The steps in most algorithms must follow a set order. Those steps are called dependencies.

算法大概会变得庞大，由于它们从差别的泉源网络大量的数据，以到达一个或多个办理方案。大多数算法的步调都一定遵照必然的次序。这些步调称为依靠项。

One example is an if/then statement. You acted like a computer algorithm when you decided how to spend your afternoon. One step was to consider the weather. IF the weather is sunny and warm, THEN you (might) choose to go outside.

举个例子便是“假如…那么…”的报告。当你决定怎样度过你的下战书时，你举动上就像一个盘算机算法。第一步是思量气候。假如气候明朗暖和，那么你大概会选择外出。

Algorithms sometimes also glean data on how people have used their computers. They may track what stories or websites people have read. Those data are used to offer these people new stories. This can be helpful if they want to see more stuff from the same source or about the same topic. Such algorithms can be harmful, however, if they prevent or in some way discourage people from seeing new or different types of information.

算法偶然也会网络人们怎样利用电脑的数据。他们大概会追踪人们读过的故事或网站。这些数据被用来为这些人提供新的故事。假如他们想看到更多来自统一泉源或关于统一主题的内容，这是很有关心的。然而，假如这些算法制止或以某种方法制止人们看到新的或差别范例的信息，那么它们大概是有害的。

We use computer algorithms for so many things. New or improved ones emerge every day. For instance, specialized ones help explain how diseases spread. Some help predict the weather. Others choose investments in the stock market.

我们在许多事变上都利用盘算机算法。每天都市显现新的或革新过的算法。比方，专门的算法有助于解说疾病是怎样流传的。一些算法关心猜测气候。其他人则选择股票市场投资。

The future will include algorithms that teach computers how to better understand more complex data. This is the beginning of what people call machine learning: computers teaching computers.

将来将包罗教盘算机怎样更好地了解更庞大的数据的算法。这便是人们所说的呆板进修的开始:盘算机教盘算机。

Another area being developed is a faster way to sort through images. There are apps that pull up possible plant names based on a photograph. Such tech currently works better on plants than it does on people. Apps that are designed to recognize faces may be fooled by haircuts, glasses, facial hair or bruises, for instance. These algorithms are still not as accurate as people tend to be. The trade-off: They’re much faster.

另一个正在开辟的范畴是快速分类图像的要领。有些应用步伐可以依据照片找出大概的植物名称。这种技能现在在植物上比在人身上更有用。比方，用于辨认人脸的应用步伐大概会被发型、眼镜、面部毛发或擦伤所诱骗。这些算法仍旧没有人们盼望的那么准确。价钱是:它们要快得多。